Is vision restoration after brain damage possible?
Humans rely on vision more than any of the other senses, and more brain tissue is devoted to visual perception than all other senses combined. Thus, when the brain is damaged, the likelihood to suffering visual impairments is high and the consequences for quality of life are grave. Loss of vision after brain damage or damage to the retina or optic nerve was long considered irreversible. However, there is a considerable potential for vision restoration and recovery even in adulthood.
How can visual functions be improved in patients with neurovisual impairment?
Today, behavioral stimulation (training) of residual vision is by far the most widely used method to stimulate the injured visual system. This includes the method of “vision restoration training” (VRT) (Kasten & Sabel, 1995; Kasten et al. 1998 a,b) which was based on the observation that repeated testing at the visual field border may induce border shifts (Zihl et al., 1979, 1985). Other laboratories have used different kinds of training paradigms, patterns of different orientations (Sahraie et al. 2006), moving spirals (Jobke et al. 2009), flickering-type stimulations (Raninen et al. 2007; Henriksson et al., 2007); Roth et al. 2009), or Gabor patches with flanker-tasks (Polat et al., 2004) or without (Sahrai et al. 2006) to train patients. There are only very few null-findings with training (Balliet et al., 1985; Reinhard et al., 2005) and no study exists that found detrimental effects.
Besides this behavioral training paradigm repetitive transcranial alternating current stimulation was shown to improve objective visual functions. This approach has been studied for two decades in Russia (Chibisova et al. 2001; Fedorov et al., 2005, 2010a, 2010b) and recently also in Germany (Sabel et al., 2010; Gall et al., 2010). By using repetitive pulses we wished to induce LTP-like enhancement of synaptic plasticity which was accomplished by transorbital current pulses at frequencies in the alpha and beta range which are capable to induce well defined phosphenes in most patients at current levels (200-400 µA) far below those needed for transcranial stimulation (1000 µA or greater) (Kanai et al., 2008).
Based on the prior Russian experience (Chibisova et al., 2001; Fedorov et al., 2005, 2010a, 2010b), these phosphenes were expected to produce clinically beneficial effects (Sabel et al., 2010; Gall et al., 2010). Most recently, the study of phosphene induction by non-invasive brain stimulations methods was initiated by other investigators. They observed that trains of transcranial alternating currents produce phosphenes in a frequency-dependent manner which is a sign of visual cortex activation (Antal et al., 2008; Kanai et al., 2010; Schutter et al., 2010).
Zaehle et al. (2010) reported that transcranial alternating current applied within the individual alpha frequency range over the visual cortex of 10 healthy subjects elevated the alpha power measured at parieto-central electrodes. This is of particular interest since increased individual alpha power is relevant for enhancing cognitive performance in normal subjects (Klimesch et al., 2003; Hanslmayr et al., 2005). This might explain why such electrical current stimulation may also enhance visual functions in patients with visual field loss (see references above).
In patients with brain damage, the improvement of visual functions in certain laboratory tests (such as perimetry) using behavioural or current stimulation may be of great interest scientifically, but unless visual field improvements are shown to be clinically relevant, contributing to a higher quality of life, clinicians will not pay much attention and patients will not become aware of this new option of vision restoration (McFadzean, 2006; Glisson & Galetta, 2007; Lane, Smith & Schenk, 2008).
How do subjective (vision-related quality of life) measures and objective visual functioning relate?
Obviously, vision loss and blindness have a negative impact on functional abilities and quality of life (McKean-Cowdin et al., 2007; Sahel et al., 2007). In patients where the visual field loss is caused by brain damage, the reduction of quality of life is mainly caused by problems in reading, driving, and peripheral vision (Gall et al, 2009). The extent of changes in vision-related quality of life is somewhat dependent on the size of visual field loss after damage to the post-chiasmatic (Papageorgiou et al., 2007; Gall et al., 2008a) or prechiasmatic pathway (Cole et al., 2000; Noble et al., 2006), or after damage to the optic chiasm – as in cases with pituitary adenoma (Okamoto et al., 2008). Particularly visual field loss and visual acuity correlate significantly with vision-related but not with health-related quality of life estimates, but the correlation is weak to moderate (Gall et al, 2009).
Objective vision impairments are typically assessed by perimetry and visual acuity tests, but this type of evaluation may fail to assess certain aspects of visual disability that are important for the daily well-being of visually impaired persons. Correlations between reports of visual functioning, generic health-related quality of life and clinical measures of visual functioning such as visual acuity are only moderate, in the order of 0.3 to 0.4, indicating that there are also other dimensions of vision that contribute to the subjective visual experience.
The National Eye Institute-Visual Functioning Questionnaire (NEI-VFQ for vision-related QoL) is perhaps the best accepted measurement of vision-related quality of life. Its correlations to generic SF-36 health-survey results are rather low, i.e. around 0.3 (Mangione et al., 1998b). This indicates that NEI-VFQ and SF-36 capture different dimensions of health. The optimal approach to measure quality of life in vision research is therefore to measure both vision-related (NEI-VFQ) and health-related (SF-36) quality of life (Franke & Gall, 2008) combined. As shown in recent years, there are possibilities to reduce visual field defects in patients with optic nerve trauma or brain damage. The clinically relevant question is this: are such restoration methods useful to lead to a better quality of life in patients?
Subjective improvements after behavioural training when stimulating the visual field border
As discussed above, there are different types of vision restoration training procedures that can improve stimulus detection in patients with post-chiasmatic and optic nerve lesions (Kasten et al., 1998a,b; Julkunen et al., 2003; Sabel et al., 2004). About 2/3 of the patients reported subjective improvements as measured in post training interviews (Mueller et al., 2003) and this is confirmed when asking patients for pre- and post-training drawings of subjective visual field sizes (Poggel et al. 2008). Other studies have developed their own methods and confirmed subjective improvements (Julkunen et al., 2003; Sabel, Kenkel & Kasten, 2004; Chokron et al., 2008).
Everyday life activities were also recorded in hemianopic patients by structured post-training interviews in a larger sample (n=69) (Mueller et al., 2003). Here, the number of patients reporting training-induced subjective improvements were as follows: reading (43.5%), ability to avoid collisions (31.9%), general vision improvement (47.8%), ability to perform hobby activities (29%), and confidence in mobility (75.4%). Objective improvements of visual field parameters correlated significantly with the number of named activities of daily living categories, but not all patients who reported subjective improvements also showed objective improvements in perimetry results, i.e. there was some “mismatch” of both kinds of measure.
This ambiguity may be, in part, due to the fact that no reliable vision-related quality of life questionnaire was used to assess treatment-induced subjective changes of self-perceived visual functioning. The more likely reason, though, is that subjective vision is a rather complex event (see discussion below) and lesion characteristics are heterogenous as are the patients` individual cognitive capacities.
To try to get a better handle on the subjective vision issue, we recently adopted the NEI-VFQ as a standardized instrument to assess vision-related quality of life and found significant improvements after visual field training in hemianopic patients (Gall et al. 2008) which were also correlated with objective perimetry results (see Figure 1). Given that questionnaires are sufficiently sensitive to detect visual field improvements, standardised questionnaires of health- and especially vision-related quality of life should be used on a regular basis in future rehabilitation studies, a recommendation also made by others (Bouwmeester, Heutink & Lucas, 2007). This will enhance our understanding of the clinical relevance of functional improvements and standardized methods can also be more easily compared between laboratories.
Figure 1: Quality of life measures were obtained in patients that suffered visual field defects after cerebral damage and that were treated with VRT. The graph shows the number of point differences in NEI-VFQ subscales after VRT as a function of changes in stimulus detection performance in computer-based high-resolution perimetric visual field tests. Patients with greater improvements in perimetry also reported greater subjective changes.
Subjective improvements after non-invasive alternating current stimulation
One may argue that patients having undergone a long and laborious training for 6 months or longer (as in vision restoration training) may be biased to report subjective visual improvements after such a substantial effort and time commitment. We therefore used a non-training type therapy, rtACS, thinking that it would be less prone to such artefacts. Before and after rtACS we have measured subjective visual functioning and vision-related quality of life and assessed self-estimated visual and health-related quality of life. rtACS led to partial restoration of visual fields which was accompanied by improvements of vision-related QoL (NEI-VFQ) and health-related QoL (SF-36).
Some, but not all, NEI-VFQ scales were sensitive to improvements in visual field size after rtACS, and particularly the subscale “general vision” improved to a clinically relevant extent in the rtACS group. The improvements were dependent on the magnitude of the visual field expansion: rtACS-treated patients with detection improvements >20% had a significantly greater increase in NEI-VFQ scores than patients with smaller detection improvements (<20%) (see Figure 2). Importantly, the rtACS effects are long-lasting, being maintained for at least 2 months and longer. Thus, rtACS is a non-invasive treatment option capable of improving visual function in the injured, adult visual system in an induring manner and this is of subjective, functional relevance to the patients` everyday life.
Figure 2: Barplot of post minus pre differences of NEI-VFQ scores general health, general vision and the NEI-VFQ composite score as a function of extent of visual field improvement (expressed as detection improvements = DA) in patients with optic nerve damage that were treated with non-invasive, repetitive, transorbitale, alternating current stimulation (rtACS). The graph shows patients with 0-20% change of detection accuracy (N=12) versus those with >20% change (N=10) after a 10-day course of rtACS.
NEI-VFQ composite score (Z=-1.25) did not differ between groups. Improvements in NEI-VFQ general health (Z=-2.24) and general vision (Z=-2.45) were significantly larger in rtACS-treated patients with >20% increase of detection accuracy compared to patients who improved less than 20%.
It is interesting to note that only some NEI-VFQ scales were sensitive to visual field expansions after visual training or rtACS. In any event, vision restoration studies ought to include assessments of vision-related quality of life, a meaningful and valuable complement to objective visual field data that better reflect on the patients` individual self-perceived situation. Because the correlations of both are modest at best, these assessments represent different aspects of vision. Another advantage of using questionnaires such as NEI-VFQ is that they help to weigh the risk (ratio of effort/cost) and benefits of interventions considering not only psychophysical status but the impact on vision-related quality of life.
Visual field impairments are typically assessed by perimetry. Here, the aim is to detect any clinically or statistically significant deviations appropriate for the respective age. However, perimetry was not designed to assess vision in every day life, and the detection of small dots presented on an ambient background is not what people see in real life every day or care much about. The visual world is much more complex comprising different shapes, colors, contours, cluttered scenes, moving objects etc. In reference to vision restoration a frequently asked question is how perimetric improvements and everyday vision relate. Also, critics claim that self-perceived training effects may be “only psychological” or “subjective” and therefore “not real”.
How do subjective and objective improvements of visual functioning relate?
We have found that there is only a rather small overlap of subjective vision and perimetric measures. In many patients perimetric improvements are associated with subjective improvements, but in other patients there is a mismatch: subjective improvements can be reported without visual field expansions and, vice versa, visual field expansions may happen without being subjectively noticed (Müller 2003). Chokron (2008) described a patient who experienced a progression of ‘subjective’ improvement after vision training despite lack of improvement in perimetry.
After vision training, the correlation coefficients between visual field expansion and improvements in everyday vision are small to moderate, at best: they rarely exceed values of r=0.4. Thus, only about 15% of subjective vision improvement can be explained by perimetric field size changes. Of course, the location and size of the scotoma has a large influence on individual subjective vision and this alone can account for some of the unexplained variance. For example, a gain of visual field size at or near fixation has a much greater subjective impact than peripheral visual field gains (Poggel et al., 2008).
But both the low correlations and the mismatch-problem raise another possibility: other factors of vision have to be considered as well. Three observations might account for some variance: (i) the “intact field” also has subtle deficits in visual cognition (contour integration), (ii) temporal processing (reaction time) is impaired, (iii) spatial resolution (visual acuity) is reduced and (iv) steady fixation of the eyes and saccades may be impaired, making the perception of stationary or moving objects more demanding (Müller et al., 2003; Paramei & Sabel. 2008; Schadow et al., 2009).
In the context of a discussion on residual vision, subjective visual improvements are therefore not easy to understand. The situation is very complex as every-day life vision is dependent on any one or a combination of several of the following factors: (i) visual field size, (ii) exact location of the field defect (foveal vs. peripheral), (iii) deficits in the “intact” field sector, (iv) temporal processing deficits, (v) decline in spatial resolution, and (vi) variable degrees of residual vision at the border zone or deep in the blind field (with unconscious elements of vision (blindsight). Furthermore, (vii) fixation accuracy and (viii) eye movements are part of the hypothesized subjective vision equation.
Thus, cases where subjective vision improves while the visual field size remains unchanged can not disprove vision restoration as being “purely psychological” or subjective. We rather propose an alternative explanation to the mismatch-problem: functions other than those tested with perimetry have improved. Indeed, vision restoration training was already shown to speed up reaction time (Kasten et al. 1995, 1998; Müller et al., 2003), increase visual acuity (e.g. Kasten et al. 1998), and improve fixation accuracy (Kasten et al. 1998). Just as subjective visual impairments are a multi-factorial and complex affair, so is the subjective improvement associated with vision restoration (Poggel et al. 2008).
Future research should include the following steps: (i) confirmation of existing therapy approaches with larger-scale clinical trials, (ii) evaluation of the versatility of such approaches to different diseases (including retinal damage), (iii) variation of treatment parameters (such as frequence any amplitude changes in electrical stimulation protocols, (iv) physiological mechanisms of vision restoration and, finally (v) imaging of brain changes induced by therapies, including local BOLT changes as well as network activations as imaged by modern high resolution MRI and network connectivity analyses (such as diffusion tensor imaging and resting state anlyses). This will then lead, in turn, to a better understanding of the mechanisms of recovery and further refinement of therapeutic appraoches with markedly improved outcomes – to the benefit of the patients every day life.
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